Knowledge graphs in manufacturing and production aim to make production lines more
efficient and flexible with higher quality output. This makes knowledge graphs attractive for …

With Knowledge Graphs (KGs) at the center of numerous applications such as recommender
systems and question-answering, the need for generalized pipelines to construct and …

Graph databases are becoming increasingly popular for modeling different kinds of
networks for data analysis. They are built over the property graph data model, where nodes …

With knowledge graphs (KGs) at the center of numerous applications such as recommender
systems and question answering, the need for generalized pipelines to construct and …

RDF triplestores and property graph databases are two approaches for data management
which are based on modeling, storing and querying graph-like data. In spite of such …

More than two decades have passed since the establishment of the initial cornerstones of
the Semantic Web. Since its inception, opinions have remained divided regarding the past …

Information related to the COVID-19 pandemic ranges from biological to bibliographic, from
geographical to genetic and beyond. The structure of the raw data is highly complex, so …

Subject to the huge semantic gap between natural and formal languages, neural semantic
parsing is typically bottlenecked by its complexity of dealing with both input semantics and …

Abstract Knowledge graphs have been widely adopted across organizations and research
domains, fueling applications that span interactive browsing to large-scale analysis and data …

The need to integrate siloed data in the built environment led to a gaining interest in
semantic web technologies in the Architecture, Engineering and Construction (AEC) sector …